# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.

# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import TYPE_CHECKING

from transformers.file_utils import _LazyModule, is_tokenizers_available, \
    is_torch_available

_import_structure = {
    "configuration_t9gpt": ["PINYINGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "T9GPTConfig"],
    "tokenization_t9gpt": ["T9GPTTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_t9gpt_fast"] = ["T9GPTTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_t9gpt"] = [
        "PINYINGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "T9GPTDoubleHeadsModel",
        "T9GPTForSequenceClassification",
        "T9GPTLMHeadModel",
        "T9GPTModel",
        "T9GPTPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_t9gpt import T9GPTConfig
    from .tokenization_t9gpt import T9GPTTokenizer

    if is_tokenizers_available():
        pass

    if is_torch_available():
        from .modeling_t9gpt import (
            T9GPTModel,
            T9GPTLMHeadModel,
        )


else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)
